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家庭病床中的被动纵向体重和心肺监测。

Passive longitudinal weight and cardiopulmonary monitoring in the home bed.

机构信息

Department of Bioengineering, Jacobs School of Engineering, University of California San Diego, 9500 Gilman Dr. MC 0412, La Jolla, CA, 92093, USA.

Division of Cardiovascular Medicine, Department of Medicine, University of California San Diego, La Jolla, CA, 92093, USA.

出版信息

Sci Rep. 2021 Dec 21;11(1):24376. doi: 10.1038/s41598-021-03105-1.

Abstract

Home health monitoring has the potential to improve outpatient management of chronic cardiopulmonary diseases such as heart failure. However, it is often limited by the need for adherence to self-measurement, charging and self-application of wearables, or usage of apps. Here, we describe a non-contact, adherence-independent sensor, that when placed beneath the legs of a patient's home bed, longitudinally monitors total body weight, detailed respiratory signals, and ballistocardiograms for months, without requiring any active patient participation. Accompanying algorithms separate weight and respiratory signals when the bed is shared by a partner or a pet. Validation studies demonstrate quantitative equivalence to commercial sensors during overnight sleep studies. The feasibility of detecting obstructive and central apneas, cardiopulmonary coupling, and the hemodynamic consequences of non-sustained ventricular tachycardia is also established. Real-world durability is demonstrated by 3 months of in-home monitoring in an example patient with heart failure and ischemic cardiomyopathy as he recovers from coronary artery bypass grafting surgery. BedScales is the first sensor to measure adherence-independent total body weight as well as longitudinal cardiopulmonary physiology. As such, it has the potential to create a multidimensional picture of chronic disease, learn signatures of impending hospitalization, and enable optimization of care in the home.

摘要

家庭健康监测有可能改善心力衰竭等慢性心肺疾病的门诊管理。然而,它通常受到需要坚持自我测量、佩戴可穿戴设备的收费和自我应用,或使用应用程序的限制。在这里,我们描述了一种非接触式、不依赖于依从性的传感器,当它放置在患者家庭床的下方时,可以在数月内纵向监测总体重、详细的呼吸信号和心冲击图,而无需患者任何主动参与。当床被伴侣或宠物共享时,伴随的算法可以分离体重和呼吸信号。验证研究表明,在夜间睡眠研究中,与商业传感器具有定量等效性。还确定了检测阻塞性和中枢性呼吸暂停、心肺耦联以及非持续性室性心动过速的血液动力学后果的可行性。在一名心力衰竭和缺血性心肌病患者从冠状动脉旁路移植手术后恢复期间,使用 BedScales 在家中进行了 3 个月的监测,证明了其实用性。BedScales 是第一个测量不依赖于依从性的总体重以及纵向心肺生理学的传感器。因此,它有可能创建慢性疾病的多维图景,学习即将住院的特征,并在家中优化护理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5747/8692625/40b31a9107ba/41598_2021_3105_Fig1_HTML.jpg

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